We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps. The resulting inferen...
Mert R. Sabuncu, B. T. Thomas Yeo, Koenraad Van Le...
In this paper, we propose a general two-dimensional hidden Markov model (2D-HMM), where dependency of the state transition probability on any state is allowed as long as causality...
We present a comparative evaluation of two data-driven models used in translation selection of English-Korean machine translation. Latent semantic analysis(LSA) and probabilistic ...
Two Dimensional Hidden Markov Models (2D-HMMs) provide substantial benefits for many computer vision and image analysis applications. Many fundamental image analysis problems, inc...
Mehmet Emre Sargin, Alphan Altinok, Kenneth Rose, ...
We propose a new method to select relevant images to the given keywords from images gathered from the Web based on the Probabilistic Latent Semantic Analysis (PLSA) model which is...